1. Field of the Invention
The present invention relates to a medical image processing apparatus and a medical image processing method, and more particularly, to a medical image processing apparatus and a medical image processing method that estimate a three-dimensional model of a living tissue based on a two-dimensional image of an image of the living tissue.
2. Description of the Related Art
Conventionally, observations have been generally performed in the medical field using image pickup apparatuses such as an X-ray diagnostic apparatus, a CT, an MRI, an ultrasound observation apparatus, and an endoscope apparatus. Among the image pickup apparatuses, the endoscope apparatus includes, for example, an insertion portion that can be inserted into the body cavity. Image pickup means such as a solid image pickup device picks up an image in the body cavity formed by an objective optical system arranged at a distal end portion of the insertion portion and outputs the image as an image pickup signal, and a graphical image of the image in the body cavity is displayed on displaying means such as a monitor based on the image pickup signal. The endoscope apparatus is operated and configured this way. The user observes an organ or the like in the body cavity based on the graphical image of the image in the body cavity displayed on the displaying means such as a monitor.
The endoscope apparatus can directly pick up an image of digestive tract mucosa. Therefore, the user can comprehensively observe, for example, color tone of mucosa, shape of lesion, and microstructure of mucosal surface.
The endoscope apparatus can also detect an image including a lesion site such as a polyp by using an image processing method, such as an image processing method described in Japanese Patent Application Laid-Open Publication No. 2005-192880 (conventional document 1), capable of detecting a predetermined image in which a lesion with locally elevated shape exists.
The image processing method described in the conventional document 1 can extract the contour of an inputted image and detect a lesion with locally elevated shape in the image based on the shape of the contour.
Conventionally, in a colonic polyp detection process, three-dimensional data is estimated from a two-dimensional image, and three-dimensional feature values (Shape Index/Curvedness) are used to detect colonic polyps (conventional document 2: Institute of Electronics, Information and Communication Engineers of Japan, IEIC Technical Report (MI2003-102), A study on automated detection of colonic polyps from 3D abdominal CT images based on shape information, Kimura, Hayashi, Kitasaka, Mori, Suenaga, pp. 29 to 34, 2004). The three-dimensional feature values are realized by calculating partial differential coefficients in a reference point based on three-dimensional data and using the partial differential coefficients. In the colonic polyp detection process, possible polyps are detected by applying a threshold process to the three-dimensional feature values.